Multiple measures, such as multiple content domains or multiple types of performance, are used in various testing programs to classify examinees for screening or selection. Despite the popular usages of multiple measures, there is little research on classification consistency and accuracy of multiple measures. Accordingly, this study introduces an…

Scoring high-dimensional assessments (e.g., > 15 traits) can be a challenging task. This paper introduces the multilabel neural network (MNN) as a scoring method for high-dimensional assessments. Additionally, it demonstrates how MNN can score the same test responses to maximize different performance metrics, such as accuracy, recall, or…

Testing programs are often interested in using a student growth measure. This article presents analytic derivations of the accuracy of common student growth measures on both the raw scale of the test and the percentile rank scale in terms of the proportional reduction in mean squared error and the squared correlation between the estimator and…

Classroom assessment and large-scale assessment have, for the most part, existed in mutual isolation. Some experts have felt this is for the best and others have been concerned that the schism limits the potential contribution of both forms of assessment. Margaret Heritage has long been a champion of best practices in classroom assessment. Neal…